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An anesthesia-integrated model for predicting postoperative urinary retention after transurethral resection of the prostate: A retrospective cohort study

Aug 2026 · Journal of International Medical Research · Vol 54 · 0 citations · 24 references
Medicine

TL;DR

The proposed anesthesia-integrated model may help identify transurethral resection of the prostate patients at increased risk of postoperative urinary retention and guide individualized perioperative bladder management.

Abstract

Objective To develop and internally validate an anesthesia-integrated prediction model for postoperative urinary retention after transurethral resection of the prostate. Methods This retrospective cohort study included 183 male patients who underwent elective transurethral resection of the prostate between January 2021 and December 2024. The primary endpoint was postoperative urinary retention occurrence within 24 h following catheter removal. Thirty-five candidate predictors spanning four domains were evaluated. Variable selection was performed using least absolute shrinkage and selection operator regression, followed by multivariable logistic regression. Model performance was assessed using the area under the receiver operating characteristic curve, calibration analysis, Brier score, bootstrap internal validation with 1000 resamples, and decision curve analysis. Results Among the 183 patients, 39 (21.3%) developed postoperative urinary retention. Seven least absolute shrinkage and selection operator–selected predictors were retained in the final model, including preoperative postvoid residual volume, history of acute urinary retention, prostate volume, high spinal block level, intraoperative opioid dose (morphine equivalent), catheter indwelling duration, and diabetes mellitus. The model achieved an area under the receiver operating characteristic curve of 0.813 in the training set and a mean bootstrap-validated area under the receiver operating characteristic curve of 0.749 (95% confidence interval: 0.625, 0.860; optimism-corrected area under the receiver operating characteristic curve: 0.731). The Brier score was 0.1287, and the calibration curve demonstrated satisfactory agreement between predicted and observed probabilities. Decision curve analysis suggested the model's clinical net benefit across a broad range of threshold probabilities. Conclusion The proposed anesthesia-integrated model may help identify transurethral resection of the prostate patients at increased risk of postoperative urinary retention and guide individualized perioperative bladder management. Prospective, multicenter external validation is warranted prior to clinical implementation.

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